Department of Mathematics
Diggle's test for complete spatial randomness of a given point pattern uses the discrepancy between the estimated and the theoretical form of a summary function as the test statistic. One commonly used discrepancy measure is the supremum of the pointwise differences over a suitably chosen range; the upper bound of the range is an arbitrary but sometimes crucial parameter. This paper shows that when we use Ripley's K -function as the summary function, it is possible to avoid using an arbitrary upper bound by using adapted distance dependent intensity estimators.
Complete spatial randomness, Edge-correction, Intensity estimator, K -function, Spatial point pattern
Source Publication Title
Journal of Statistical Computation and Simulation
Taylor & Francis
This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Statistical Computation and Simulation in July 2006, available online: http://dx.doi.org/10.1080/00949650412331321043.
This research was supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. HKBU2048/02P) and an FRG grant of the Hong Kong Baptist University.
Link to Publisher's Edition
Ho, L., & Chiu, S. (2006). Testing the complete spatial randomness by Diggle's test without an arbitrary upper limit. Journal of Statistical Computation and Simulation, 7 (76), 585-591. https://doi.org/10.1080/00949650412331321043